Dicas de visualizacao

library(tidyverse, warn.conflicts = FALSE)

── Attaching packages ────────────────────────────────────────── tidyverse 1.2.1 ──
✔ ggplot2 3.0.0     ✔ purrr   0.2.5
✔ tibble  1.4.2     ✔ dplyr   0.7.6
✔ tidyr   0.8.1     ✔ stringr 1.3.1
✔ readr   1.1.1     ✔ forcats 0.3.0
── Conflicts ───────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

theme_set(theme_bw())

Os dados

gastos_bruto = read_csv("../dados/ano-atual.csv", progress = FALSE)

Parsed with column specification:
cols(
  .default = col_integer(),
  sgPartido = col_character(),
  txtCNPJCPF = col_character(),
  vlrGlosa = col_double(),
  txNomeParlamentar = col_character(),
  sgUF = col_character(),
  vlrDocumento = col_double(),
  txtDescricaoEspecificacao = col_character(),
  datEmissao = col_datetime(format = ""),
  txtDescricao = col_character(),
  txtNumero = col_character(),
  txtFornecedor = col_character(),
  vlrLiquido = col_double(),
  txtPassageiro = col_character(),
  txtTrecho = col_character(),
  vlrRestituicao = col_character()
)
See spec(...) for full column specifications.

gastos = gastos_bruto %>% 
  mutate(txtDescricao = ifelse(txtDescricao == "Emissão Bilhete Aéreo", 
                               "PASSAGENS AÉREAS", 
                               txtDescricao))

Gastos ao longo do tempo

gastos.por.mes = gastos %>% 
  filter(numMes < 6) %>% 
  group_by(numMes, txtDescricao) %>% 
  summarize(total = sum(vlrDocumento) / 1e6) 
ggplot(gastos.por.mes, aes(x = numMes, y = total, colour = txtDescricao)) +
  labs(x = "Mês de 2016", y = "Gastos em Milhões") +
  geom_line()

library(directlabels)
ggplot(gastos.por.mes, aes(x = numMes, y = total, colour = txtDescricao)) +
  labs(x = "Mês de 2016", y = "Gastos em Milhões") +
  geom_line() + 
  theme(legend.position="none") + 
  geom_dl(aes(label = txtDescricao), method = "last.points", cex = 0.5) + 
  xlim(1, 10)

ggplot(gastos.por.mes, aes(x = numMes, y = total, colour = txtDescricao)) +
  labs(x = "Mês de 2016", y = "Gastos em Milhões") +
  geom_line() + 
  facet_wrap(~ txtDescricao, ncol = 4) + 
  theme(legend.position="none", strip.text.x = element_text(hjust = 0, size = 8))

E por dia?

library(lubridate)

Attaching package: ‘lubridate’

The following object is masked from ‘package:base’:

    date

gastos.por.dia = gastos %>% 
  filter(numMes < 6) %>% 
  mutate(dia = day(datEmissao)) %>% 
  group_by(dia, txtDescricao) %>% 
  summarize(total = sum(vlrDocumento) / 1e3) %>% # Em milhares
  mutate(txtDescricao = as.factor(txtDescricao))

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ggplot(gastos.por.dia, aes(x = dia, y = total, colour = txtDescricao)) +
  labs(x = "Mês de 2016", y = "Gastos em Milhões") +
  geom_line() + 
  facet_wrap(~ txtDescricao, ncol = 4) + 
  theme(legend.position="none", strip.text.x = element_text(hjust = 0, size = 8))

E por dia e mês?

gastos.dia.mes = gastos %>% 
  filter(numMes < 6) %>% 
  mutate(dia = day(datEmissao)) %>% 
  group_by(dia, numMes, txtDescricao) %>% 
  summarize(total = sum(vlrDocumento) / 1e3) %>% # Em milhares
  mutate(txtDescricao = as.factor(txtDescricao))

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ggplot(gastos.dia.mes, aes(x = dia, y = total, colour = txtDescricao, group = numMes)) +
  labs(x = "Mês de 2016", y = "Gastos em milhares de R$") +
  geom_line() + 
  facet_wrap(~ txtDescricao, ncol = 4) + 
  theme(legend.position="none", strip.text.x = element_text(hjust = 0, size = 8))

ggplot(gastos.dia.mes, aes(x = dia, y = total, colour = txtDescricao, group = numMes)) +
  labs(x = "Mês de 2016", y = "Gastos em milhares de R$") +
  geom_line(alpha = .5) + 
  facet_wrap(~ txtDescricao, ncol = 4) + 
  theme(legend.position="none", strip.text.x = element_text(hjust = 0, size = 8))

Ordenar sempre ajuda a leitura

media.mensal = gastos %>% 
  filter(numMes<6) %>%
  group_by(sgUF, txNomeParlamentar) %>% 
  summarize(media = mean(vlrDocumento))
estados = media.mensal %>% 
  group_by(sgUF) %>% 
  summarise(media = mean(media))
(ggplot(media.mensal, mapping = aes(x = sgUF, y = media, colour = sgUF)) +
  geom_point(aes(label = txNomeParlamentar), position = position_jitter(width = 0.25), alpha = 0.4, na.rm = TRUE)+
  theme(legend.position="none") + 
  geom_point(data = estados, colour = "black", size = 1.5, shape = 18) +
  labs( y ="media de gasto mensal", x= "Estado")) %>%
  ggplotly()

Ignoring unknown aesthetics: label

media.mensal = left_join(media.mensal, estados, by = c("sgUF"))
names(media.mensal) = c("sgUF", "txNomeParlamentar", "media", "media.estado")
ggplot(media.mensal, mapping = aes(x = reorder(sgUF, -media.estado), y = media, colour = sgUF))+
  geom_point(position = position_jitter(width = 0.25), alpha = 0.4, na.rm = TRUE)+
  theme(legend.position="none") + 
  geom_point(data = estados, aes(x = sgUF, y = media), colour = "black", size = 1.5, shape = 18) +
  labs( y ="media de gasto mensal", x= "Estado")

ggplotly(ggplot(media.mensal, mapping = aes(x = reorder(sgUF, -media.estado), y = media, colour = sgUF))+
  geom_violin(alpha = 0.3) + 
  geom_point(position = position_jitter(width = 0.25), alpha = 0.4, na.rm = TRUE)+
  theme(legend.position="none") + 
  geom_point(data = estados, aes(x = sgUF, y = media), colour = "black", size = 1.5, shape = 18) +
  labs( y ="media de gasto mensal", x= "Estado"))